The OncoSim-Breast Cancer Microsimulation Model.

BACKGROUND: OncoSim-Breast is a Canadian breast cancer simulation model to evaluate breast cancer interventions. This paper aims to describe the OncoSim-Breast model and how well it reproduces observed breast cancer trends. METHODS: The OncoSim-Breast model simulates the onset, growth, and spread of invasive and ductal carcinoma in situ tumours. It combines Canadian cancer incidence, mortality, screening program, and cost data to project population-level outcomes. Users can change the model input to answer specific questions. Here, we compared its projections with observed data. First, we compared the model's projected breast cancer trends with the observed data in the Canadian Cancer Registry and from Vital Statistics. Next, we replicated a screening trial to compare the model's projections with the trial's observed screening effects. RESULTS: OncoSim-Breast's projected incidence, mortality, and stage distribution of breast cancer were close to the observed data in the Canadian Cancer Registry and from Vital Statistics. OncoSim-Breast also reproduced the breast cancer screening effects observed in the UK Age trial. CONCLUSIONS: OncoSim-Breast's ability to reproduce the observed population-level breast cancer trends and the screening effects in a randomized trial increases the confidence of using its results to inform policy decisions related to early detection of breast cancer.

Single-shot phase contrast microscopy using polarisation-resolved differential phase contrast.

We present a robust, low-cost single-shot implementation of differential phase microscopy utilising a polarisation-sensitive camera to simultaneously acquire four images from which phase contrast images can be calculated. This polarisation-resolved differential phase contrast (pDPC) microscopy technique can be easily integrated with fluorescence microscopy.

Clinical impact and cost-effectiveness of integrating smoking cessation into lung cancer screening: a microsimulation model.

BACKGROUND: Low-dose computed tomography (CT) screening can reduce lung cancer mortality in people at high risk; adding a smoking cessation intervention to screening could further improve screening program outcomes. This study aimed to assess the impact of adding a smoking cessation intervention to lung cancer screening on clinical outcomes, costs and cost-effectiveness. METHODS: Using the OncoSim-Lung mathematical microsimulation model, we compared the projected lifetime impact of a smoking cessation intervention (nicotine replacement therapy, varenicline and 12 wk of counselling) in the context of annual low-dose CT screening for lung cancer in people at high risk to lung cancer screening without a cessation intervention in Canada. The simulated population consisted of Canadians born in 1940-1974; lung cancer screening was offered to eligible people in 2020. In the base-case scenario, we assumed that the intervention would be offered to smokers up to 10 times; each intervention would achieve a 2.5% permanent quit rate. Sensitivity analyses varied key model inputs. We calculated incremental cost-effectiveness ratios with a lifetime horizon from the health system's perspective, discounted at 1.5% per year. Costs are in 2019 Canadian dollars. RESULTS: Offering a smoking cessation intervention in the context of lung cancer screening could lead to an additional 13% of smokers quitting smoking. It could potentially prevent 12 more lung cancers and save 200 more life-years for every 1000 smokers screened, at a cost of $22 000 per quality-adjusted life-year (QALY) gained. The results were most sensitive to quit rate. The intervention would cost over $50 000 per QALY gained with a permanent quit rate of less than 1.25% per attempt. INTERPRETATION: Adding a smoking cessation intervention to lung cancer screening is likely cost-effective. To optimize the benefits of lung cancer screening, health care providers should encourage participants who still smoke to quit smoking.

A Phase I Study of DLYE5953A, an Anti-LY6E Antibody Covalently Linked to Monomethyl Auristatin E, in Patients with Refractory Solid Tumors.

PURPOSE: DLYE5953A is an antibody-drug conjugate consisting of an anti-LY6E antibody covalently linked to the cytotoxic agent monomethyl auristatin E. This study characterized the safety, pharmacokinetics, immunogenicity, potential biomarkers, and antitumor activity of DLYE5953A in patients with metastatic solid tumors. PATIENTS AND METHODS: This was a phase I, open-label, 3+3 dose-escalation, and dose-expansion study of DLYE5953A administered intravenously every 21 days (Q3W) in patients with locally advanced or metastatic solid malignancies. RESULTS: Sixty-eight patients received DLYE5953A (median, four cycles; range, 1-27). No dose-limiting toxicities were identified during dose escalation (0.2-2.4 mg/kg; n = 20). The recommended phase II dose (RP2D) of 2.4 mg/kg Q3W was based on overall safety and tolerability. Dose-expansion cohorts for HER2-negative metastatic breast cancer (HER2-negative MBC; n = 23) and non-small cell lung cancer (NSCLC; n = 25) patients were enrolled at the RP2D. Among patients receiving DLYE5953A 2.4 mg/kg (n = 55), the most common (≥30%) related adverse events (AEs) included alopecia, fatigue, nausea, and peripheral neuropathy. Grade ≥3 related AEs occurred in 14 of 55 (26%) patients, with neutropenia being the most common (13%). DLYE5953A demonstrated linear total antibody pharmacokinetics at doses of ≥0.8 mg/kg with low unconjugated monomethyl auristatin E levels in blood. Partial response was confirmed in eight of 68 (12%) patients, including three of 29 patients with MBC (10%) and five of 25 patients with NSCLC (20%) at the RP2D. Stable disease was the best response for 37 of 68 (54%) patients. CONCLUSIONS: DLYE5953A administered at 2.4 mg/kg has acceptable safety. Preliminary evidence of antitumor activity in patients with HER2-negative MBC and NSCLC supports further investigation of LY6E as a therapeutic target.

A text message delivered smoking cessation intervention: Design and rationale of the Text My Quit Study.

INTRODUCTION: Smoking cessation interventions delivered through mobile technologies offer promise as an effective intervention tool. However, most existing programs have not been empirically tested, were not developed with end-user participation, and/or do not address evidence-based cognitive and behavioral variables shown to enhance smoking cessation in clinical trials. In addition, many programs tested in research trials have required users to access the internet and/or a smartphone app to access all program features, limiting the potential reach of those programs. METHODS/DESIGN: This study is a randomized controlled trial testing the efficacy of the TMQ intervention for smoking cessation. All participants are randomly assigned to receive 12 weeks of either; (1) a tailored smoking-cessation intervention delivered 100% through text messaging (TMQ), or (2) non-smoking-related text messages serving as a control for contact and subject burden (Mojo). Assessments are conducted at baseline, 3- and 6-month follow-up. The primary outcome is prolonged abstinence using an intent-to-treat approach. To understand why TMQ may be more effective than Mojo, we will test several posited mechanisms of action (i.e., mediators) that may underlie intervention efficacy and will examine use of the TMQ integrated social support (ISS) network. At the end of treatment, semi-structured interviews will be conducted with TMQ participants. CONCLUSIONS: This study will provide a rigorous test of an innovative smoking cessation program delivered 100% through text messages. Use of mixed methodologies will provide the opportunity to enhance our understanding of the user's experience with TMQ and identify areas for future enhancement and/or expansion.

Development and Validation of the Evaluation Platform in COPD (EPIC): A Population-Based Outcomes Model of COPD for Canada.

BACKGROUND: We report the development, validation, and implementation of an open-source population-based outcomes model of chronic obstructive pulmonary disease (COPD) for Canada. METHODS: Evaluation Platform in COPD (EPIC) is a discrete-event simulation model of Canadians 40 years of age or older. Three core features of EPIC are its open-population design (incorporating projections of future population growth, aging, and smoking trends), its incorporation of heterogeneity in lung function decline and burden of exacerbations, and its modeling of the natural history of COPD from inception. Multiple original data analyses, as well as values reported in the literature, were used to populate the model. Extensive face validity and internal and external validity evaluations were performed. RESULTS: The model was internally validated on demographic projections, mortality rates, lung function trajectories, COPD exacerbations, costs and health state utility values, and stability of COPD prevalence over time within strata of risk factors. In external validation, it moderately overestimated the rate of overall exacerbations in 2 independent trials but generated consistent estimates of rate of severe exacerbations and mortality. LIMITATIONS: In its current version, EPIC does not consider uncertainty in the evidence. Several components such as additional (e.g., environmental and occupational) risk factors, treatment, symptoms, and comorbidity will have to be added in future iterations. Predictive validity of EPIC needs to be examined prospectively against future empirical studies. CONCLUSIONS: EPIC is the first multipurpose, open-source, outcome- and policy-focused model of COPD for Canada. Platforms of this type have the capacity to be iteratively updated to incorporate the latest evidence and to project the outcomes of many different scenarios within a consistent framework.

Development of a population-based microsimulation model of body mass index.

BACKGROUND: The increasing prevalence of overweight and obesity has necessitated the development of body mass index (BMI) projection models such as the POpulation HEalth Model (POHEM). This study describes the POHEM-BMI model, a microsimulation tool that can be used to support evidence-based health policy making for obesity reduction. DATA AND METHODS: The National Population Health Survey, the Canadian Community Health Survey (CCHS), and the Canadian Health Measures Survey (CHMS) were used to develop and validate a predictive model of BMI for adults and childhood BMI history. Models were incorporated into POHEM and used to transition BMI over time in a fully dynamic simulated Canadian population. RESULTS: POHEM-BMI projections of self-reported and measured adult BMI and childhood BMI history agree well with CCHS and CHMS validation estimates. Among men and women, average BMI is projected to increase by more than one BMI unit between 2001 and 2030. Projections of self-reported BMI show that 59% of the adult population will be overweight or obese by 2030; projections of measured BMI show that the percentage will be 66%. INTERPRETATION: Using empirically developed BMI prediction models for adults and childhood BMI history integrated into the POHEM framework, validated projections of BMI for the Canadian population can be produced. Projections of BMI trends could have important applications in tracking the prevalence of related diseases, and in planning and comparing intervention strategies.

Alzheimer's and other dementias in Canada, 2011 to 2031: a microsimulation Population Health Modeling (POHEM) study of projected prevalence, health burden, health services, and caregiving use.

BACKGROUND: Worldwide, there is concern that increases in the prevalence of dementia will result in large demands for caregivers and supportive services that will be challenging to address. Previous dementia projections have either been simple extrapolations of prevalence or macrosimulations based on dementia incidence. METHODS: A population-based microsimulation model of Alzheimer's and related dementias (POHEM:Neurological) was created using Canadian demographic data, estimates of dementia incidence, health status (health-related quality of life and mortality risk), health care costs and informal caregiving use. Dementia prevalence and 12 other measures were projected to 2031. RESULTS: Between 2011 and 2031, there was a projected two-fold increase in the number of people living with dementia in Canada (1.6-fold increase in prevalence rate). By 2031, the projected informal (unpaid) caregiving for dementia in Canada was two billion hours per year, or 100 h per year per Canadian of working age. CONCLUSIONS: The projected increase in dementia prevalence was largely related to the expected increase in older Canadians, with projections sensitive to changes in the age of dementia onset.

Biennial lung cancer screening in Canada with smoking cessation-outcomes and cost-effectiveness.

BACKGROUND: Guidelines recommend low-dose CT (LDCT) screening to detect lung cancer among eligible at-risk individuals. We used the OncoSim model (formerly Cancer Risk Management Model) to compare outcomes and costs between annual and biennial LDCT screening. METHODS: OncoSim incorporates vital statistics, cancer registry data, health survey and utility data, cost, and other data, and simulates individual lives, aggregating outcomes over millions of individuals. Using OncoSim and National Lung Screening Trial eligibility criteria (age 55-74, minimum 30 pack-year smoking history, smoking cessation less than 15 years from time of first screen) and data, we have modeled screening parameters, cancer stage distribution, and mortality shifts for screen diagnosed cancer. Costs (in 2008 Canadian dollars) and quality of life years gained are discounted at 3% annually. RESULTS: Compared with annual LDCT screening, biennial screening used fewer resources, gained fewer life-years (61,000 vs. 77,000), but resulted in very similar quality-adjusted life-years (QALYs) (24,000 vs. 23,000) over 20 years. The incremental cost-effectiveness ratio (ICER) of annual compared with biennial screening was $54,000-$4.8 million/QALY gained. Average incremental CT scan use in biennial screening was 52% of that in annual screening. A smoking cessation intervention decreased the average cost-effectiveness ratio in most scenarios by half. CONCLUSIONS: Over 20 years, biennial LDCT screening for lung cancer appears to provide similar benefit in terms of QALYs gained to annual screening and is more cost-effective. Further study of biennial screening should be undertaken in population screening programs. A smoking cessation program should be integrated into either screening strategy.

Risk of work loss due to illness or disability in patients with osteoarthritis: a population-based cohort study.

OBJECTIVES: To estimate the risk of work loss due to illness or disability in a cohort of employed persons with OA compared with matched non-OA individuals. METHODS: We performed a population-based cohort analysis using the last six cycles of the Canadian longitudinal National Population Health Survey from 2000 to 2010. OA cases and up to four age- and sex-matched non-OA individuals were selected. Discrete time hazard regression models were used to estimate the hazard of work loss due to illness or disability. To analyse the effect of a self-reported OA measure on the outcome, we performed a sensitivity analyses for case selection. RESULTS: From 7273 employed individuals between the ages of 20 and 70 years in the National Population Health Survey, 659 OA cases were selected and matched to 2144 non-OA individuals. The proportion of OA cases who experienced work loss due to illness or disability during the follow-up period was 12.6%, compared with 9.3% for non-OA individuals (P < 0.001). OA cases had a 90% [hazard ratio (HR) 1.90 (95% CI 1.36, 3.23)] higher hazard of work loss due to illness or disability compared with their matched non-OA individuals after adjusting for sociodemographic, health and work-related status. The adjusted HRs were 1.61 (95% CI 1.13, 2.30) and 2.04 (95% CI 1.74, 4.75) for females and males, respectively. CONCLUSION: OA is independently associated with an increased risk of work loss due to illness or disability. Given the high prevalence of OA in the population of working age, future research may wish to investigate ways to improve occupational participation among OA patients.

Effects of Reductions in Body Mass Index on the Future Osteoarthritis Burden in Canada: A Population-Based Microsimulation Study.

OBJECTIVE: Osteoarthritis (OA) is the most common joint disease and a major cause of disability. Incidence and prevalence of OA are expected to increase due to population aging and increased levels of obesity. The purpose of this study was to project the effect of hypothetical interventions that change the distribution of body mass index (BMI) on OA burden in Canada. METHODS: We used a microsimulation computer model of OA based on the Population Health Model platform. The model used demographic predictions for Canada and population data from an administrative database in British Columbia and national Canadian surveys. RESULTS: Under the base-case scenario, between 2010 and 2030, OA prevalence is expected to increase from 11.5% to 15.6% in men and 16.3% to 21.1% in women. In scenarios assuming, on average, a 0.3-, 0.5-, or 1-unit drop in BMI per year, OA prevalence in 2030 would reach 14.9%, 14.6%, and 14.2% in men and 20.3%, 19.7%, and 18.5%, in women, respectively. Under these scenarios, the proportion of new cases prevented would be 9.5%, 13.2%, and 16.7%, respectively, in men, and 9.1%, 15.2%, and 25.0% in women. Targeting only those people ages ≥50 years for weight reduction would achieve approximately 70% of the impact of a full population strategy. Targeting only the obese (BMI ≥30) would likely result in a larger benefit for men than women. CONCLUSION: Due to the aging of the population, OA will remain a major and growing health issue in Canada over the next 2 decades, regardless of the course of the obesity epidemic.

The Population Health Model (POHEM): an overview of rationale, methods and applications.

The POpulation HEalth Model (POHEM) is a health microsimulation model that was developed at Statistics Canada in the early 1990s. POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals' disease states, risk factors, and health determinants, in order to describe and project health outcomes, including disease incidence, prevalence, life expectancy, health-adjusted life expectancy, quality of life, and healthcare costs. Additionally, POHEM was conceptualized and built with the ability to assess the impact of policy and program interventions, not limited to those taking place in the healthcare system, on the health status of Canadians. Internationally, POHEM and other microsimulation models have been used to inform clinical guidelines and health policies in relation to complex health and health system problems. This paper provides a high-level overview of the rationale, methodology, and applications of POHEM. Applications of POHEM to cardiovascular disease, physical activity, cancer, osteoarthritis, and neurological diseases are highlighted.

Cost-effectiveness of Lung Cancer Screening in Canada.

IMPORTANCE: The US National Lung Screening Trial supports screening for lung cancer among smokers using low-dose computed tomographic (LDCT) scans. The cost-effectiveness of screening in a publically funded health care system remains a concern. OBJECTIVE: To assess the cost-effectiveness of LDCT scan screening for lung cancer within the Canadian health care system. DESIGN, SETTING, AND PARTICIPANTS: The Cancer Risk Management Model (CRMM) simulated individual lives within the Canadian population from 2014 to 2034, incorporating cancer risk, disease management, outcome, and cost data. Smokers and former smokers eligible for lung cancer screening (30 pack-year smoking history, ages 55-74 years, for the reference scenario) were modeled, and performance parameters were calibrated to the National Lung Screening Trial (NLST). The reference screening scenario assumes annual scans to age 75 years, 60% participation by 10 years, 70% adherence to screening, and unchanged smoking rates. The CRMM outputs are aggregated, and costs (2008 Canadian dollars) and life-years are discounted 3% annually. MAIN OUTCOMES AND MEASURES: The incremental cost-effectiveness ratio. RESULTS: Compared with no screening, the reference scenario saved 51,000 quality-adjusted life-years (QALY) and had an incremental cost-effectiveness ratio of CaD $52,000/QALY. If smoking history is modeled for 20 or 40 pack-years, incremental cost-effectiveness ratios of CaD $62,000 and CaD $43,000/QALY, respectively, were generated. Changes in participation rates altered life years saved but not the incremental cost-effectiveness ratio, while the incremental cost-effectiveness ratio is sensitive to changes in adherence. An adjunct smoking cessation program improving the quit rate by 22.5% improves the incremental cost-effectiveness ratio to CaD $24,000/QALY. CONCLUSIONS AND RELEVANCE: Lung cancer screening with LDCT appears cost-effective in the publicly funded Canadian health care system. An adjunct smoking cessation program has the potential to improve outcomes.

Performance of the cancer risk management model lung cancer screening module.

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography (LDCT) screening reduces lung cancer mortality in a high-risk U.S. population. A microsimulation model of LDCT screening was developed to estimate the impact of introducing population-based screening in Canada. DATA AND METHODS: LDCT screening was simulated using the lung cancer module of the Cancer Risk Management Model (CRMM-LC), which generates large, representative samples of the Canadian population from which a cohort with characteristics similar to NLST participants was selected. Screening parameters were estimated for stage shift, LDCT sensitivity and specificity, lead time, and survival to fit to NLST incidence and mortality results. The estimation process was a step-wise directed search. RESULTS: Simulated mortality reduction from LDCT screening was 23% in the CRMM-LC, compared with 20% in the NLST. The difference in the number of lung cancer cases over six years varied by, at most, 2.3% in the screen arm. The difference in cumulative incidence at six years was less than 2% in both screen and control arms. The estimated percentage over-diagnosed was 24.8%, which was 6% higher than NLST results. INTERPRETATION: Simulated screening reproduces NLST results. The CRMM-LC can evaluate a variety of population-based screening strategies. Sensitivity analyses are recommended to provide a range of projections to reflect model uncertainty.

Eligibility for low-dose computerized tomography screening among asbestos-exposed individuals.

OBJECTIVES: The study aimed to incorporate an estimate of risk for asbestos exposure in the Canadian Cancer Risk Management Lung Cancer (CRMM-LC) microsimulation model. METHODS: In CRMM-LC, a 3-year probability of developing lung cancer can be derived from different risk profiles. An asbestos-exposed cohort was simulated and different scenarios of low-dose computerized tomography (LDCT) screening were simulated. RESULTS: As annual LDCT screening among non-asbestos-exposed individuals is less cost-effective than biennial screening, all the scenarios modeled for an asbestos-exposed cohort were biennial. For individuals with a two-fold risk of asbestos-induced lung cancer to be eligible for biennial LDCT screening, a smoking history of ≥15 pack-years would be necessary. For non-smokers with asbestos exposure resulting in a relative risk (RR) for lung cancer, it is not cost-effective to screen those with a RR of 5, but it is cost-effective to screen those with a RR of 10 (the heavily exposed). CONCLUSION: Asbestos-exposed individuals with an estimated two-fold or more risk of lung cancer from asbestos-exposure are eligible for LDCT screening at all ages from 55-74 years if they have a cigarette smoking history of ≥15 pack-years. Asbestos-exposed individuals who are lifelong non-smokers are eligible for LDCT screening at all ages from 55-74 years if they have accumulated a degree of asbestos exposure resulting in an estimated risk of lung cancer of ≥10.

Illustrating anticipatory life cycle assessment for emerging photovoltaic technologies.

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Projections of preventable risks for cardiovascular disease in Canada to 2021: a microsimulation modelling approach.

BACKGROUND: Reductions in preventable risks associated with cardiovascular disease have contributed to a steady decrease in its incidence over the past 50 years in most developed countries. However, it is unclear whether this trend will continue. Our objective was to examine future risk by projecting trends in preventable risk factors in Canada to 2021. METHODS: We created a population-based microsimulation model using national data on births, deaths and migration; socioeconomic data; cardiovascular disease risk factors; and algorithms for changes in these risk factors (based on sociodemographic characteristics and previous cardiovascular disease risk). An initial population of 22.5 million people, representing the Canadian adult population in 2001, had 13 characteristics including the risk factors used in clinical risk prediction. There were 6.1 million potential exposure profiles for each person each year. Outcome measures included annual prevalence of risk factors (smoking, obesity, diabetes, hypertension and lipid levels) and of co-occurring risks. RESULTS: From 2003 to 2009, the projected risks of cardiovascular disease based on the microsimulation model closely approximated those based on national surveys. Except for obesity and diabetes, all risk factors were projected to decrease through to 2021. The largest projected decreases were for the prevalence of smoking (from 25.7% in 2001 to 17.7% in 2021) and uncontrolled hypertension (from 16.1% to 10.8%). Between 2015 and 2017, obesity was projected to surpass smoking as the most prevalent risk factor. INTERPRETATION: Risks of cardiovascular disease are projected to decrease modestly in Canada, leading to a likely continuing decline in its incidence.